TEAM

Founded in May 2011 by two Stanford Alumni, Blue River Technology is bringing Computer Vision and Machine Learning expertise into the technical agriculture space. The idea was conceived during a class taught by Steve Blank at Stanford and funded by Investors including Khosla Ventures as well as through an ﻿SBIR grant by the National Science Foundation﻿

Jorge is an accomplished professional in the areas of High-Technology and Precision Agriculture. Jorge worked at Trimble Navigation for over 14 years as Business Unit Director for the Precision Agriculture Unit, Director of Business Development and Director of Engineering. While at these roles, Jorge created and led high-performing teams that have delivered over 20 high-technology products to the Agriculture market place including Automatic Guidance for agricultural vehicles, GPS receivers, and Rate Controllers. He also headed 4 acquisitions in high-technology agriculture.

Lee Redden has experience at the leading edge of robotics, computer vision and machine learning. He has performed research at robotics labs at Johns Hopkins Applied Physics Lab, NASA Johnson Space Center, Stanford University, and the University of Nebraska-Lincoln. Lee is an NSF Graduate Research Fellowship and NASA Space Grant Scholarship recipient.

Lee was the team lead for the NASA Robotics Academy hosted by Goddard Space Flight Center, where components of a computer vision based novel locomotion robot was developed. Lee was the idea generator for Stanford’s Summer Institute of Entrepreneurship, an intensive business school training program targeted to students with technical training. Many business models around computer vision and machine learning were generated and pitched to venture capitalists.

Lee holds a BS in Mechanical Engineering from the University of Nebraska-Lincoln, and an MS in Mechanical Engineering from Stanford University with depth in mechatronics systems. He has completed his second year of PhD studies at Stanford University, and is currently on a leave of absence from that program.

This company is based upon work supported by the National Science Foundation under Grant No. 1143463